Haibin Lin

3.0k citations
18 papers · 1.2k indexed · 1 hit paper · h-index 8
Topics
Advanced Neural Network Applications (7 papers)Topic Modeling (3 papers)Computer Graphics and Visualization Techniques (3 papers)

In The Last Decade

Haibin Lin

13 papers receiving 1.2k citations

Hit Papers

ResNeSt: Split-Attention Networks20222026202320242022200400600

Peers

Haibin Lin
Comparison fields: 5 of 143
  • Computer Vision and Pattern Recognition 502
  • Artificial Intelligence 455
  • Computer Networks and Communications 179
  • Information Systems 131
  • Media Technology 103
Replace Brian C. Van Essen with:
Brian C. Van Essen United States
Yuxing Peng China
Pengzhen Ren Australia
Mohd. Samar Ansari India
Zhonglong Zheng China
Yun Xiao China
Suk‐Hwan Lee South Korea
Vasileios Argyriou United Kingdom
Zhi Zhang China
Haibin Lin relative to Brian C. Van Essen United States Brian C. Van Essen's profile →
Citations per field
00.5×3.1×
Brian C. Van Essen · 1×
Citations per year

Countries citing papers authored by Haibin Lin

Since Specialization
Citations

This map shows the geographic impact of Haibin Lin's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Haibin Lin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Haibin Lin more than expected).

Fields of papers citing papers by Haibin Lin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Haibin Lin. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Haibin Lin. The network helps show where Haibin Lin may publish in the future.

Co-authorship network of co-authors of Haibin Lin

This figure shows the co-authorship network connecting the top 25 collaborators of Haibin Lin. A scholar is included among the top collaborators of Haibin Lin based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Haibin Lin. Haibin Lin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

18 of 18 papers shown
#WorkIndexed citations
1 0
2 0
3 0
4 1
5 8
6 45
7 0
8 1
9 14
10
ResNeSt: Split-Attention Networksbreakdown →
629
11
GluonCV and GluonNLP: Deep Learning in Computer Vision and Natural Language Processing
109
12
CSER: Communication-efficient SGD with Error Reset.
6
13 36
14
Deep Graph Library: Towards Efficient and Scalable Deep Learning on Graphs
260
15
Self-Driving Database Management Systems.
130
16 1
17 0
18 3

About Haibin Lin

Haibin Lin is a scholar working on Computational Mathematics, Computer Graphics and Computer-Aided Design and Computer Vision and Pattern Recognition, having authored 18 papers that have together received 1.2k indexed citations. Recurring topics across this work include Advanced Neural Network Applications (7 papers), Topic Modeling (3 papers) and Computer Graphics and Visualization Techniques (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (502 citations), Artificial Intelligence (455 citations) and Media Technology (103 citations). Haibin Lin has collaborated with scholars based in China, United States and Germany. Frequent co-authors include Alexander J. Smola, Mu Li, Tong He, Yi Zhu, Zhongyue Zhang, Hang Zhang, Jonas Mueller, Yue Sun, Zhi Zhang and R. Manmatha. Their work appears in journals such as Scientific Reports, Chemical Engineering Journal and Talanta.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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